Abstract: An audio object including audio content and object metadata is received. The object metadata indicates an object spatial position of the audio object to be rendered by audio speakers in a playback environment. Based on the object spatial position and source spatial positions of the audio speakers, initial gain values for the audio speakers are determined. The initial gain values can be used to select a set of audio speakers from among the audio speakers. Based on the object spatial position and a set of source spatial positions at which the set of audio speakers are respectively located in the playback environment, a set of non-negative optimized gain values for the set of audio speakers is determined. The audio object at the object spatial position is rendered with the set of optimized gain values for the set of audio speakers.

Abstract: Embodiments relate to audio processing unit(s) and methods for decoding an encoded audio bitstream, that includes a fill element with an identifier indicating a start of the fill element and fill data which includes a flag identifying whether to perform a base form of spectral band replication or an enhanced form of spectral band replication, wherein the base form of spectral band replication includes spectral patching, the enhanced form of spectral band replication includes harmonic transposition, one value of the flag indicates that said enhanced form of spectral band replication should be performed on the audio content, and another indicates that said base form of spectral band replication but not said harmonic transposition should be performed on the audio content, wherein the fill data further includes a parameter indicating whether pre-flattening is to be performed after spectral patching for avoiding spectral discontinuities.

Abstract: A neural network system is provided, implementing a generative model for autoregressively generating a distribution for a plurality of current filter-bank samples of an audio signal, wherein the current samples correspond to a current time slot, and each current sample corresponds to a channel of the filter-bank. The system includes a hierarchy of a plurality of neural network processing tiers ordered from a top to a bottom tier, each tier trained to generate conditioning information based on previous filter-bank samples and, for at least each tier but the top tier, also on the conditioning information from a tier higher up in the hierarchy, and an output stage trained to generate the probability distribution based on previous samples for one or more previous time slots and the conditioning information from the lowest processing tier.

Abstract: A neural network system for predicting frequency coefficients of a media signal, the neural network system comprising a time predicting portion including at least one neural network trained to predict a first set of output variables representing a specific frequency band of a current time frame given coefficients of one or several previous time frames, and a frequency predicting portion including a at least one neural network trained to predict a second set of output variables representing a specific frequency band given coefficients of one or several frequency bands adjacent to the specific frequency band in said current time frame. Such a neural network system forms a predictor capable of capturing both temporal and frequency dependencies occurring in time-frequency tiles of a media signal.

Abstract: The present invention relates to transposing signals in time and/or frequency and in particular to coding of audio signals. More particular, the present invention relates to high frequency reconstruction (HFR) methods including a frequency domain harmonic transposer. A method and system for generating a transposed output signal from an input signal using a transposition factor T is described. The system comprises an analysis window of length La, extracting a frame of the input signal, and an analysis transformation unit of order M transforming the samples into M complex coefficients. M is a function of the transposition factor T. The system further comprises a nonlinear processing unit altering the phase of the complex coefficients by using the transposition factor T, a synthesis transformation unit of order M transforming the altered coefficients into M altered samples, and a synthesis window of length Ls, generating a frame of the output signal.

Abstract: The present disclosure provides methods, devices and computer program products for non-uniform quantization of parameters. The disclosure further relates to a method and apparatus for reconstructing an audio object in an audio decoding system taking the non-uniformly quantized parameters into account. According to the disclosure, such an approach renders it possible to reduce bit consumption without substantially reducing the quality of the reconstructed audio object.

Abstract: The present document describes a method (400) for personalizing audio content. The method (400) comprises receiving (401) a manifest file (140) for the audio content. The manifest file (140) comprises at least one adaptation set (281, 282) referencing an audio bitstream (121), where the audio bitstream (121) comprises a plurality of audio objects (181), and a plurality of different preselection elements (291, 292, 293) for the adaptation set (281, 282), wherein the different preselection elements (291, 292, 293) specify different combinations of the plurality of audio objects (181). The method (400) further comprises selecting (402) a preselection element (291) from the plurality of different preselection elements (291, 292, 293), and causing (403) rendering of an audio signal which depends on the selected preselection element (291).

Abstract: A method for decoding a video bitstream is disclosed. The method comprises: entropy decoding a first portion of a video bitstream, wherein first portion of video bitstream is associated with a video frame, thereby producing a first portion of decoded data; entropy decoding a second portion of video bitstream, wherein second portion of video bitstream is associated with video frame, thereby producing a second portion of decoded data, wherein entropy decoding second portion of video bitstream is independent of entropy decoding first portion of video bitstream; and reconstructing a first portion of video frame associated with video bitstream using first portion of decoded data and second portion of decoded data.

Abstract: The disclosure relates to methods, apparatus and systems for side load processing of packetized media streams. In an embodiment, the apparatus comprises: a receiver for receiving a bitstream, and a splitter for identifying a packet type in the bitstream and splitting, based on the identification of a value of the packet type in the bit stream into a main stream and an auxiliary stream.

Abstract: Embodiments are directed to a companding method and system for reducing coding noise in an audio codec. A method of processing an audio signal includes the following operations. A system receives an audio signal. The system determines that a first frame of the audio signal includes a sparse transient signal. The system determines that a second frame of the audio signal includes a dense transient signal. The system compresses/expands (compands) the audio signal using a companding rule that applies a first companding exponent to the first frame of the audio signal and applies a second companding exponent to the second frame of the audio signal, each companding exponent being used to derive a respective degree of dynamic range compression and expansion for a corresponding frame. The system then provides the companded audio signal to a downstream device.

Abstract: A method for decoding an encoded audio bitstream is disclosed. The method includes receiving the encoded audio bitstream and decoding the audio data to generate a decoded lowband audio signal. The method further includes extracting high frequency reconstruction metadata and filtering the decoded lowband audio signal with an analysis filterbank to generate a filtered lowband audio signal. The method also includes extracting a flag indicating whether either spectral translation or harmonic transposition is to be performed on the audio data and regenerating a highband portion of the audio signal using the filtered lowband audio signal and the high frequency reconstruction metadata in accordance with the flag. The high frequency regeneration is performed as a post-processing operation with a delay of 3010 samples per audio channel.

Abstract: A method for decoding an encoded audio bitstream in an audio processing system is disclosed. The method includes extracting from the encoded audio bitstream a first waveform-coded signal comprising spectral coefficients corresponding to frequencies up to a first cross-over frequency for a time frame and performing parametric decoding at a second cross-over frequency for the time frame to generate a reconstructed signal. The second cross-over frequency is above the first cross-over frequency and the parametric decoding uses reconstruction parameters derived from the encoded audio bitstream to generate the reconstructed signal. The method also includes extracting from the encoded audio bitstream a second waveform-coded signal comprising spectral coefficients corresponding to a subset of frequencies above the first cross-over frequency for the time frame and interleaving the second waveform-coded signal with the reconstructed signal to produce an interleaved signal for the time frame.

Abstract: The present disclosure relates to a method and system for performing packet loss concealment using a neural network system. The method comprises obtaining a representation of an incomplete audio signal, inputting the representation of the incomplete audio signal to an encoder neural network and outputting a latent representation of a predicted complete audio signal. The latent representation is input to a decoder neural network which outputs a representation of a predicted complete audio signal comprising a reconstruction of the original portion of the complete audio signal, wherein said encoder neural network and said decoder neural network have been trained with an adversarial neural network.

Abstract: A method for decoding an encoded audio bitstream is disclosed. The method includes receiving the encoded audio bitstream and decoding the audio data to generate a decoded lowband audio signal. The method further includes extracting high frequency reconstruction metadata and filtering the decoded lowband audio signal with an analysis filterbank to generate a filtered lowband audio signal. The method also includes extracting a flag indicating whether either spectral translation or harmonic transposition is to be performed on the audio data and regenerating a highband portion of the audio signal using the filtered lowband audio signal and the high frequency reconstruction metadata in accordance with the flag.

Abstract: A method for decoding an encoded audio bitstream is disclosed. The method includes receiving the encoded audio bitstream and decoding the audio data to generate a decoded lowband audio signal. The method further includes extracting high frequency reconstruction metadata and filtering the decoded lowband audio signal with an analysis filterbank to generate a filtered lowband audio signal. The method also includes extracting a flag indicating whether either spectral translation or harmonic transposition is to be performed on the audio data and regenerating a highband portion of the audio signal using the filtered lowband audio signal and the high frequency reconstruction metadata in accordance with the flag. The high frequency regeneration is performed as a post-processing operation with a delay of 3010 samples per audio channel.

Abstract: A method for decoding an encoded audio bitstream is disclosed. The method includes receiving the encoded audio bitstream and decoding the audio data to generate a decoded lowband audio signal. The method further includes extracting high frequency reconstruction metadata and filtering the decoded lowband audio signal with an analysis filterbank to generate a filtered lowband audio signal. The method also includes extracting a flag indicating whether either spectral translation or harmonic transposition is to be performed on the audio data and regenerating a highband portion of the audio signal using the filtered lowband audio signal and the high frequency reconstruction metadata in accordance with the flag. The high frequency regeneration is performed as a post-processing operation with a delay of 3010 samples per audio channel.

Abstract: A method for decoding an encoded audio bitstream is disclosed. The method includes receiving the encoded audio bitstream and decoding the audio data to generate a decoded lowband audio signal. The method further includes extracting high frequency reconstruction metadata and filtering the decoded lowband audio signal with an analysis filterbank to generate a filtered lowband audio signal. The method also includes extracting a flag indicating whether either spectral translation or harmonic transposition is to be performed on the audio data and regenerating a highband portion of the audio signal using the filtered lowband audio signal and the high frequency reconstruction metadata in accordance with the flag. The high frequency regeneration is performed as a post-processing operation with a delay of 3010 samples per audio channel.

Abstract: Embodiments relate to an audio processing unit that includes a buffer, bitstream payload deformatter, and a decoding subsystem. The buffer stores at least one block of an encoded audio bitstream. The block includes a fill element that begins with an identifier followed by fill data. The fill data includes at least one flag identifying whether enhanced spectral band replication (eSBR) processing is to be performed on audio content of the block. A corresponding method for decoding an encoded audio bitstream is also provided.

Abstract: The invention provides an efficient implementation of cross-product enhanced high-frequency reconstruction (HFR), wherein a new component at frequency Q?+r?0 is generated on the basis of existing components at ? and ?+?0. The invention provides a block-based harmonic transposition, wherein a time block of complex subband samples is processed with a common phase modification. Superposition of several modified samples has the net effect of limiting undesirable intermodulation products, thereby enabling a coarser frequency resolution and/or lower degree of oversampling to be used. In one embodiment, the invention further includes a window function suitable for use with block-based cross-product enhanced HFR. A hardware embodiment of the invention may include an analysis filter bank, a subband processing unit configurable by control data and a synthesis filter bank.

Abstract: The present document relates to audio coding systems. In particular, the present document relates to efficient methods and systems for parametric multi-channel audio coding. An audio encoding system configured to generate a bitstream indicative of a downmix signal and spatial metadata for generating a multi-channel upmix signal from the downmix signal is described. The system comprises a downmix processing unit configured to generate the downmix signal from a multi-channel input signal; wherein the downmix signal comprises m channels and wherein the multi-channel input signal comprises n channels; n, m being integers with m<n. Furthermore, the system comprises a parameter processing unit configured to determine the spatial metadata from the multi-channel input signal.